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Application of environmental sensitivity theories in personalized prevention for youth substance abuse: a transdisciplinary translational perspective

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Translational Behavioral Medicine

Abstract

Preventive interventions that target high-risk youth, via one-size-fits-all approaches, have demonstrated modest effects in reducing rates of substance use. Recently, substance use researchers have recommended personalized intervention strategies. Central to these approaches is matching preventatives to characteristics of an individual that have been shown to predict outcomes. One compelling body of literature on person × environment interactions is that of environmental sensitivity theories, including differential susceptibility theory and vantage sensitivity. Recent experimental evidence has demonstrated that environmental sensitivity (ES) factors moderate substance abuse outcomes. We propose that ES factors may augment current personalization strategies such as matching based on risk factors/severity of problem behaviors (risk severity (RS)). Specifically, individuals most sensitive to environmental influence may be those most responsive to intervention in general and thus need only a brief-type or lower-intensity program to show gains, while those least sensitive may require more comprehensive or intensive programming for optimal responsiveness. We provide an example from ongoing research to illustrate how ES factors can be incorporated into prevention trials aimed at high-risk adolescents.

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References

  1. Swendsen J, Burstein M, Case B, et al. Use and abuse of alcohol and illicit drugs in US adolescents: results of the National Comorbidity Survey-Adolescent Supplement. Arch Gen Psychiatry. 2012; 69(4): 390-398.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Waldron HB, Turner CW. Evidence-based psychosocial treatments for adolescent substance abuse. J Clin Child Adolesc Psychol. 2008; 37(1): 238-261.

    Article  PubMed  Google Scholar 

  3. Cornelius JR, Maisto SA, Pollock NK, et al. Rapid relapse generally follows treatment for substance use disorders among adolescents. Addict Behav. 2003; 28(2): 381-386.

    Article  PubMed  Google Scholar 

  4. Muñoz RF, Mrazek PJ, Haggerty RJ. Institute of Medicine report on prevention of mental disorders. Summary and commentary. Am Psychol. 1996; 51(11): 1116-1122.

    Article  PubMed  Google Scholar 

  5. Sussman S, Dent CW, Stacy AW. Project towards no drug abuse: a review of the findings and future directions. Am J Health Behav. 2002; 26(5): 354-365.

    Article  PubMed  Google Scholar 

  6. Eggert LL, Thompson EA, Herting JR, et al. Reconnecting youth to prevent drug abuse, school dropout, and suicidal behaviors among high-risk youth. Innovations in Adolescent Substance Abuse Intervention. Oxford: Elsevier Science; 2001: 51-84.

    Google Scholar 

  7. Dishion TJ, Kavanagh K, Schneiger A, et al. Preventing early adolescent substance use: a family-centered strategy for the public middle school. Prev Sci. 2002; 3(3): 191-201.

    Article  PubMed  Google Scholar 

  8. Sandler I, Wolchik SA, Cruden G, et al. Overview of meta-analyses of the prevention of mental health, substance use, and conduct problems. Annu Rev Clin Psychol. 2014; 10: 243-273.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Fishbein DH, Ridenour TA. Advancing transdisciplinary translation for prevention of high-risk behaviors: introduction to the special issue. Prev Sci. 2013; 14(3): 201-205.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Kranzler HR, Mckay JR. Personalized treatment of alcohol dependence. Curr Psychiatry Rep. 2012; 14(5): 486-493.

    Article  PubMed  Google Scholar 

  11. Murphy SA, Collins LM, Rush AJ. Customizing treatment to the patient: adaptive treatment strategies. Drug Alcohol Depend. 2007; 88(Suppl 2): S1-S3.

    Article  PubMed  PubMed Central  Google Scholar 

  12. August GJ, Piehler TF, Bloomquist ML. Being “SMART” about adolescent conduct problems prevention: executing a SMART pilot study in a juvenile diversion agency. J Clin Child Adolesc Psychol. 2014;1–15.

  13. D’amico EJ, Fromme K. Brief prevention for adolescent risk-taking behavior. Addiction. 2002; 97(5): 563-574.

    Article  PubMed  Google Scholar 

  14. Leeder JS, Spielberg SP. Personalized medicine: reality and reality checks. Ann Pharmacother. 2009; 43(5): 963-966.

    Article  PubMed  Google Scholar 

  15. Conrod PJ, Castellanos N, Mackie C. Personality-targeted interventions delay the growth of adolescent drinking and binge drinking. J Child Psychol Psychiatry. 2008; 49(2): 181-190.

    PubMed  Google Scholar 

  16. Schuckit MA, Kalmijn JA, Smith TL, et al. Structuring a college alcohol prevention program on the low level of response to alcohol model: a pilot study. Alcohol Clin Exp Res. 2012; 36(7): 1244-1252.

    Article  PubMed  Google Scholar 

  17. Sussman S, Valente TW, Rohrbach LA, et al. Translation in the health professions—converting science into action. Eval Health Prof. 2006; 29(1): 7-32.

    Article  PubMed  Google Scholar 

  18. Dodge KA, Conduct Problems Prevention Research Group. Fast track randomized controlled trial to prevent externalizing psychiatric disorders: findings from grades 3 to 9. J Am Acad Child Adolesc Psychiatry. 2007; 46(10): 1250-1262.

    Article  Google Scholar 

  19. Kadden R, Carbonari J, Litt M, et al. Matching alcoholism treatments to client heterogeneity: project MATCH three-year drinking outcomes. Alcohol Clin Exp Res. 1998; 22: 1300-1311.

    Google Scholar 

  20. Larimer ME, Cronce JM. Identification, prevention and treatment: a review of individual-focused strategies to reduce problematic alcohol consumption by college students. J Stud Alcohol Suppl. 2002; 14: 148-163.

    Article  PubMed  Google Scholar 

  21. Pluess M. Individual differences in environmental sensitivity. Child Dev Perspect. In-press.

  22. Aron EN, Aron A. Sensory-processing sensitivity and its relation to introversion and emotionality. J Pers Soc Psychol. 1997; 73(2): 345-368.

    Article  CAS  PubMed  Google Scholar 

  23. Boyce WT, Ellis BJ. Biological sensitivity to context: I. An evolutionary-developmental theory of the origins and functions of stress reactivity. Dev Psychopathol. 2005; 17(2): 271-301.

    Article  PubMed  Google Scholar 

  24. Pluess M, Belsky J. Vantage sensitivity: individual differences in response to positive experiences. Psychol Bull. 2013; 139(4): 901-916.

    Article  PubMed  Google Scholar 

  25. Monroe SM, Simons AD. Diathesis-stress theories in the context of life stress research: implications for the depressive disorders. Psychol Bull. 1991; 110(3): 406-425.

    Article  CAS  PubMed  Google Scholar 

  26. Ellis BJ, Boyce WT, Belsky J, et al. Differential susceptibility to the environment: an evolutionary-neurodevelopmental theory. Dev Psychopathol. 2011; 23(1): 7-28.

    Article  PubMed  Google Scholar 

  27. Bakermans-Kranenburg MJ, van IJzendoorn MH. Research review: genetic vulnerability or differential susceptibility in child development: the case of attachment. J Child Psychol Psychiatry. 2007; 48(12): 1160-1173.

    Article  PubMed  Google Scholar 

  28. Belsky J, Pluess M. Beyond diathesis stress: differential susceptibility to environmental influences. Psychol Bull. 2009; 135(6): 885-908.

    Article  PubMed  Google Scholar 

  29. Ellis BJ, Essex MJ, Boyce WT. Biological sensitivity to context: II. Empirical explorations of an evolutionary-developmental theory. Dev Psychopathol. 2005; 17(2): 303-328.

    Article  PubMed  Google Scholar 

  30. Belsky J, van IJzendoorn MH. What works for whom? Genetic moderation of intervention efficacy. Dev Psychopathol. 2015; 27(01): 1-6.

    Article  PubMed  Google Scholar 

  31. Brody GH, Beach SRH, Hill KG, et al. Using genetically informed, randomized prevention trials to test etiological hypotheses about child and adolescent drug use and psychopathology. Am J Public Health. 2013; 103: S19-S24.

    Article  PubMed  PubMed Central  Google Scholar 

  32. van IJzendoorn MH, Bakermans-Kranenburg MJ. Differential susceptibility experiments: going beyond correlational evidence: comment on beyond mental health: differential susceptibility articles. Dev Psychol. 2012; 48(3): 769-774.

    Article  PubMed  Google Scholar 

  33. Bakermans-Kranenburg MJ, Van IJzendoorn MH, Pijlman FTA, et al. Experimental evidence for differential susceptibility: dopamine D4 receptor polymorphism (DRD4 VNTR) moderates intervention effects on toddlers’ externalizing behavior in a randomized controlled trial. Dev Psychol. 2008; 44(1): 293-300.

    Article  PubMed  Google Scholar 

  34. Brody GH, Beach SRH, Philibert RA, et al. Prevention effects moderate the association of 5-HTTLPR and youth risk behavior initiation: gene x environment hypotheses tested via a randomized prevention design. Child Dev. 2009; 80(3): 645-661.

    Article  PubMed  Google Scholar 

  35. Bakermans-Kranenburg MJ, van IJzendoorn MH. Differential susceptibility to rearing environment depending on dopamine-related genes: new evidence and a meta-analysis. Dev Psychopathol. 2011; 23(1): 39-52.

    Article  PubMed  Google Scholar 

  36. van IJzendoorn MH, Bakermans-Kranenburg MJ, Belsky J, et al. Gene-by-environment experiments: a new approach to finding the missing heritability. Nat Rev Genet. 2011; 12(12): 881.

    Article  CAS  PubMed  Google Scholar 

  37. Velderman MK, Bakermans-Kranenburg MJ, Juffer F, et al. Effects of attachment-based interventions on maternal sensitivity and infant attachment: differential susceptibility of highly reactive infants. J Fam Psychol. 2006; 20(2): 266-274.

    Article  PubMed  Google Scholar 

  38. Anzman-Frasca S, Stifter CA, Paul IM, et al. Negative temperament as a moderator of intervention effects in infancy: testing a differential susceptibility model. Prevent Sci. 2013: 1–11.

  39. Blair C. Early intervention for low birth weight, preterm infants: the role of negative emotionality in the specification of effects. Dev Psychopathol. 2002; 14(2): 311-332.

    Article  PubMed  Google Scholar 

  40. Cassidy J, Woodhouse SS, Sherman LJ, et al. Enhancing infant attachment security: an examination of treatment efficacy and differential susceptibility. Dev Psychopathol. 2011; 23(1): 131-148.

    Article  PubMed  Google Scholar 

  41. Beach SRH, Brody GH, Lei MK, et al. Differential susceptibility to parenting among African American youths: testing the DRD4 hypothesis. J Fam Psychol. 2010; 24(5): 513-521.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Brody GH, Chen YF, Beach SRH, et al. Differential sensitivity to prevention programming: a dopaminergic polymorphism-enhanced prevention effect on protective parenting and adolescent substance use. Health Psychol. 2014; 33(2): 182-191.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Brody GH, Chen YF, Beach SRH. Differential susceptibility to prevention: GABAergic, dopaminergic, and multilocus effects. J Child Psychol Psychiatry. 2013; 54(8): 863-871.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Brody GH, Yu T, Beach SRH. A differential susceptibility analysis reveals the “who and how” about adolescents’ responses to preventive interventions: tests of first-and second-generation gene × intervention hypotheses. Dev Psychopathol. 2015; 27(01): 37-49.

    Article  PubMed  PubMed Central  Google Scholar 

  45. van IJzendoorn MH, Bakermans-Kranenburg MJ. Genetic differential susceptibility on trial: meta-analytic support from randomized controlled experiments. Dev Psychopathol. 2015; 27(01): 151-162.

    Article  PubMed  Google Scholar 

  46. Cicchetti D, Rogosch FA, Toth SL. The effects of child maltreatment and polymorphisms of the serotonin transporter and dopamine D4 receptor genes on infant attachment and intervention efficacy. Dev Psychopathol. 2011; 23(2): 357-372.

    Article  PubMed  Google Scholar 

  47. Beevers CG, McGeary JE. Therapygenetics: moving towards personalized psychotherapy treatment. Trends Cogn Sci. 2012; 16(1): 11-12.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Belsky J, Pluess M. Beyond risk, resilience, and dysregulation: phenotypic plasticity and human development. Dev Psychopathol. 2013; 25(4): 1243-1261.

    Article  PubMed  Google Scholar 

  49. HSC Scale © 2011 M. Pluess, J. Bakker, S. Walda, A. Bosman, E. Aron & A. Aron.

  50. Obradović J, Bush NR, Boyce WT. The interactive effect of marital conflict and stress reactivity on externalizing and internalizing symptoms: the role of laboratory stressors. Dev Psychopathol. 2011; 23(01): 101-114.

    Article  PubMed  Google Scholar 

  51. Eisenberg N, Sulik MJ, Spinrad TL, et al. Differential susceptibility and the early development of aggression: interactive effects of respiratory sinus arrhythmia and environmental quality. Dev Psychol. 2012; 48(3): 755.

    Article  PubMed  PubMed Central  Google Scholar 

  52. van de Wiel NMH, van Goozen SHM, Matthys W, et al. Cortisol and treatment effect in children with disruptive behavior disorders: a preliminary study. J Am Acad Child Adolesc Psychiatry. 2004; 43(8): 1011-1018.

    Article  PubMed  Google Scholar 

  53. Van IJzendoorn MH, Belsky J, Bakermans-Kranenburg MJ. Serotonin transporter genotype 5HTTLPR as a marker of differential susceptibility? A meta-analysis of child and adolescent gene-by-environment studies. Transl Psychiatry. 2012; 2(8), e147.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Cicchetti D, Toth SL, Handley ED. Genetic moderation of interpersonal psychotherapy efficacy for low-income mothers with major depressive disorder: implications for differential susceptibility. Dev Psychopathol. 2015; 27(01): 19-35.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Dick DM et al. Candidate gene-environment interaction research: reflections and recommendations. Perspect Psychol Sci. 2015; 10(1): 37-59.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Cicchetti D, Dawson G. Editorial: multiple levels of analysis. Dev Psychopathol. 2002; 14(03): 417-420.

    Article  PubMed  Google Scholar 

  57. Howe GW, Beach SRH, Brody GH. Microtrial methods for translating gene-environment dynamics into preventive interventions. Prev Sci. 2010; 11(4): 343-354.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Bakermans-Kranenburg MJ, Van IJzendoorn MH. The hidden efficacy of interventions: gene × environment experiments from a differential susceptibility perspective. Annu Rev Psychol. 2015; 66: 381-409.

    Article  PubMed  Google Scholar 

  59. Winters KC, Leitten W. Brief interventions for moderate drug abusing adolescents. Psychol Addict Behav. 2007; 21: 151-156.

    Article  Google Scholar 

  60. Dishion TJ, Stormshak EA, Kavanagh K. Everyday parenting: a therapist’s guide for supporting family management practice. Eugene, OR: Child and Family Center Publications; 2010.

    Google Scholar 

  61. Stanger C, Ryan SR, Fu HY, et al. Delay discounting predicts adolescent substance abuse treatment outcome. Exp Clin Psychopharmacol. 2012; 20(3): 205-212.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Almirall D, Compton SN, Gunlicks-stoessel M, et al. Designing a pilot sequential multiple assignment randomized trial for developing an adaptive treatment strategy. Stat Med. 2012; 31(17): 1887-1902.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

The research described in this manuscript is a product an on ongoing research project conducted by Eric Thibodeau, a pre-doctoral training fellow in a T32 Training Program in Translational Prevention Science sponsored by the National Institute of Mental Health, T32 MH010026 (awarded to Gerald August, Ph.D.). We wish to acknowledge Michael Pluess,  Marinus van IJzendoorn, and Geertjan Overbeek for their helpful comments as this concept was being developed.

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Authors and Affiliations

  1. University of Minnesota, Minneapolis, MN, USA

    Eric L. Thibodeau, Gerald J. August, Dante Cicchetti & Frank J. Symons

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  1. Eric L. Thibodeau
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  2. Gerald J. August
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  3. Dante Cicchetti
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  4. Frank J. Symons
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Correspondence to Eric L. Thibodeau.

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All authors of this submitted manuscript agreed to comply with all ethical principals as set forth by Translational Behavioral Medicine including the following:

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Implications

Practitioner: Measuring environmental sensitivity as a moderator of intervention response may lead to the development of a screening tool that prevention practitioners can use to tailor the type or dosage of preventatives to their high-risk clients.

Policy Maker: Personalized preventive interventions informed by indices of environmental sensitivity may increase the efficiency of interventions, minimize burden, and reduce costs, all of which have important implications for policy.

Researcher: Researchers are encouraged to incorporate indices of environmental sensitivity into ongoing prevention research to explore novel, innovative, translational-informed moderation effects.

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Thibodeau, E.L., August, G.J., Cicchetti, D. et al. Application of environmental sensitivity theories in personalized prevention for youth substance abuse: a transdisciplinary translational perspective. Behav. Med. Pract. Policy Res. 6, 81–89 (2016). https://doi.org/10.1007/s13142-015-0374-4

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